iPhone 15 Pro
Geekbench ML Score
6102
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | April 27 2024 08:16 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.4.1 |
| Model | iPhone 15 Pro |
| Model ID | iPhone16,1 |
| Motherboard | D83AP |
| CPU Information | |
|---|---|
| Name | Apple A17 Pro |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 3.78 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| L1 Instruction Cache | 128 KB x 1 |
| L1 Data Cache | 64.0 KB x 1 |
| L2 Cache | 4.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 7.47 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1246
233.1 IPS |
|
|
Image Classification (F16)
|
100% |
6270
1.17 KIPS |
|
|
Image Classification (I8)
|
99% |
6974
1.31 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1472
24.6 IPS |
|
|
Image Segmentation (F16)
|
100% |
1843
30.8 IPS |
|
|
Image Segmentation (I8)
|
100% |
1847
30.8 IPS |
|
|
Pose Estimation (F32)
|
100% |
14883
18.0 IPS |
|
|
Pose Estimation (F16)
|
100% |
82527
99.9 IPS |
|
|
Pose Estimation (I8)
|
100% |
86516
104.8 IPS |
|
|
Object Detection (F32)
|
100% |
1486
111.0 IPS |
|
|
Object Detection (F16)
|
100% |
3932
293.5 IPS |
|
|
Object Detection (I8)
|
97% |
1624
121.3 IPS |
|
|
Face Detection (F32)
|
100% |
6367
75.7 IPS |
|
|
Face Detection (F16)
|
97% |
10623
126.3 IPS |
|
|
Face Detection (I8)
|
96% |
10586
125.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
12467
96.7 IPS |
|
|
Depth Estimation (F16)
|
100% |
38331
297.3 IPS |
|
|
Depth Estimation (I8)
|
37% |
49131
381.0 IPS |
|
|
Style Transfer (F32)
|
100% |
29755
39.1 IPS |
|
|
Style Transfer (F16)
|
100% |
116397
153.1 IPS |
|
|
Style Transfer (I8)
|
100% |
120438
158.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
7200
257.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
17832
636.8 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
17972
641.8 IPS |
|
|
Text Classification (F32)
|
100% |
641
920.8 IPS |
|
|
Text Classification (F16)
|
100% |
498
715.9 IPS |
|
|
Text Classification (I8)
|
96% |
324
465.6 IPS |
|
|
Machine Translation (F32)
|
100% |
751
13.8 IPS |
|
|
Machine Translation (F16)
|
100% |
1549
28.5 IPS |
|
|
Machine Translation (I8)
|
99% |
686
12.6 IPS |
